Journal article
Text and Structural Data Mining of Influenza Mentions in Web and Social Media
International journal of environmental research and public health, Vol.7(2), pp.596-615
02/2010
Handle:
https://hdl.handle.net/2376/105038
PMCID: PMC2872292
PMID: 20616993
Abstract
Text and structural data mining of web and social media (WSM) provides a novel disease surveillance resource and can identify online communities for targeted public health communications (PHC) to assure wide dissemination of pertinent information. WSM that mention influenza are harvested over a 24-week period, 5 October 2008 to 21 March 2009. Link analysis reveals communities for targeted PHC. Text mining is shown to identify trends in flu posts that correlate to real-world influenza-like illness patient report data. We also bring to bear a graph-based data mining technique to detect anomalies among flu blogs connected by publisher type, links, and user-tags.
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Details
- Title
- Text and Structural Data Mining of Influenza Mentions in Web and Social Media
- Creators
- Courtney D Corley - Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USADiane J Cook - School of Electrical Engineering and Computer Science, Washington State University, PO Box 642752 Pullman, Washington 99164, USA; E-MailArmin R Mikler - Department of Computer Science and Engineering, University of North Texas, 1155 Union Circle #311366 Denton, TX 76203, USA; E-MailKaran P Singh - Department of Biostatistics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd. Fort Worth, TX 76107, USA; E-Mail
- Publication Details
- International journal of environmental research and public health, Vol.7(2), pp.596-615
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Publisher
- Molecular Diversity Preservation International (MDPI)
- Identifiers
- 99900547080601842
- Language
- English
- Resource Type
- Journal article